18,089 research outputs found
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Geovisualization of dynamics, movement and change: key issues and developing approaches in visualization research
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Evaluating the appropriateness of visually combining quantitative data representations with 3D desktop virtual environments using mixed methods
The State of the Art in Cartograms
Cartograms combine statistical and geographical information in thematic maps,
where areas of geographical regions (e.g., countries, states) are scaled in
proportion to some statistic (e.g., population, income). Cartograms make it
possible to gain insight into patterns and trends in the world around us and
have been very popular visualizations for geo-referenced data for over a
century. This work surveys cartogram research in visualization, cartography and
geometry, covering a broad spectrum of different cartogram types: from the
traditional rectangular and table cartograms, to Dorling and diffusion
cartograms. A particular focus is the study of the major cartogram dimensions:
statistical accuracy, geographical accuracy, and topological accuracy. We
review the history of cartograms, describe the algorithms for generating them,
and consider task taxonomies. We also review quantitative and qualitative
evaluations, and we use these to arrive at design guidelines and research
challenges
Evaluating Cartogram Effectiveness
Cartograms are maps in which areas of geographic regions (countries, states)
appear in proportion to some variable of interest (population, income).
Cartograms are popular visualizations for geo-referenced data that have been
used for over a century and that make it possible to gain insight into patterns
and trends in the world around us. Despite the popularity of cartograms and the
large number of cartogram types, there are few studies evaluating the
effectiveness of cartograms in conveying information. Based on a recent task
taxonomy for cartograms, we evaluate four major different types of cartograms:
contiguous, non-contiguous, rectangular, and Dorling cartograms. Specifically,
we evaluate the effectiveness of these cartograms by quantitative performance
analysis, as well as by subjective preferences. We analyze the results of our
study in the context of some prevailing assumptions in the literature of
cartography and cognitive science. Finally, we make recommendations for the use
of different types of cartograms for different tasks and settings
Label size design : aesthetics and effeciency
Considering label as one of the important map component, this paper is an attempt to provide empirical evidence of label size design rules and frames which is based on the design aesthetics and efficiency. Determining the ‘best’ legible label size is critical concern involves testing design aspect and needs. Both aesthetics and efficiency can set the design frames for better perception and legibility. Aesthetics was calculated by determining users´ preference of different use of label sizes, whereas efficiency was calculated by measuring time to locate targets of different. Both areal and point data were involved in the study to determine the combination of the two measurements of label size design. Digital maps were designed and presented to users as they were firstly asked about their preference of different use of label size, and secondly they were asked to locate different label size. The intersection between the first test and the second one attributes the frames for label size design. The correlation between the preferable sizes and the efficient sizes is being traced and the relation between label size aesthetics and efficiency is being identified. This study indicates the need to test other visual variable in order to serve many labelling functions
Investigating the effectiveness of an efficient label placement method using eye movement data
This paper focuses on improving the efficiency and effectiveness of dynamic and interactive maps in relation to the user. A label placement method with an improved algorithmic efficiency is presented. Since this algorithm has an influence on the actual placement of the name labels on the map, it is tested if this efficient algorithms also creates more effective maps: how well is the information processed by the user. We tested 30 participants while they were working on a dynamic and interactive map display. Their task was to locate geographical names on each of the presented maps. Their eye movements were registered together with the time at which a given label was found. The gathered data reveal no difference in the user's response times, neither in the number and the duration of the fixations between both map designs. The results of this study show that the efficiency of label placement algorithms can be improved without disturbing the user's cognitive map. Consequently, we created a more efficient map without affecting its effectiveness towards the user
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Building bridges between methodological approaches: a meta-framework linking experiments and applied studies in 3D geovisualization research
Evaluating the usability of a visual feature modeling notation
International audienceFeature modeling is a popular Software Product Line Engineering (SPLE) technique used to describe variability in a product family. A usable feature modeling tool environment should enable SPLE practitioners to produce good quality models, in particular, models that effectively communicate modeled information. FAMILIAR is a text-based environment for manipulating and composing Feature Models (FMs). In this paper we present extensions we made to FAMILIAR to enhance its usability. The extensions include a visualization of FMs, or more precisely , a feature diagram rendering mechanism that supports the use of a combination of text and graphics to describe FMs, their configurations, and the results of FM analyses. We also present the results of a preliminary evaluation of the environment's usability. The evaluation involves comparing the use of the extended environment with the previous text-based console-driven version. The preliminary experiment provides some evidence that use of the new environment results in increased cognitive effectiveness of novice users and improved quality of new FMs
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